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<li class="navelem"><a class="el" href="dir_5956a3e80a20e8e03eb577bedb92689f.html">gpu</a></li><li class="navelem"><a class="el" href="dir_2be73404b46ec2282840cd36fdb9a907.html">impl</a></li>  </ul>
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<div class="title">BinaryDistance.cu</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/**</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) Facebook, Inc. and its affiliates.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * This source code is licensed under the MIT license found in the</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * LICENSE file in the root directory of this source tree.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;</div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceTensor.cuh&quot;</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceDefs.cuh&quot;</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="preprocessor">#include &quot;../utils/DeviceUtils.h&quot;</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="preprocessor">#include &quot;../utils/Select.cuh&quot;</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;</div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="keyword">namespace </span>faiss { <span class="keyword">namespace </span>gpu {</div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;</div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment">// Number of warps that the kernel is instantiated with</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;constexpr <span class="keywordtype">int</span> kWarps = 8;</div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;constexpr <span class="keywordtype">int</span> kLanes = kWarpSize;</div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;</div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;constexpr <span class="keywordtype">int</span> kMaxDistance = std::numeric_limits&lt;int&gt;::max();</div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;</div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment">// Performs a binary matrix multiplication, returning the lowest k results in</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment">// `vecs` for each `query` in terms of Hamming distance (a fused kernel)</span></div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment">// Each warp calculates distance for a single query</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NumWarpQ,</div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;          <span class="keywordtype">int</span> NumThreadQ,</div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;          <span class="keyword">typename</span> BinaryType&gt;</div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;__launch_bounds__(kWarps * kLanes)</div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;__global__ <span class="keywordtype">void</span> binaryDistanceAnySize(<span class="keyword">const</span> Tensor&lt;BinaryType, 2, true&gt; vecs,</div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;                                      <span class="keyword">const</span> Tensor&lt;BinaryType, 2, true&gt; query,</div>
<div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;                                      Tensor&lt;int, 2, true&gt; outK,</div>
<div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;                                      Tensor&lt;int, 2, true&gt; outV,</div>
<div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;                                      <span class="keywordtype">int</span> k) {</div>
<div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;  <span class="comment">// A matrix tile (query, k)</span></div>
<div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;  __shared__ BinaryType queryTile[kWarps][kLanes + 1]; <span class="comment">// avoid bank conflict</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;</div>
<div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;  <span class="comment">// B matrix tile (vec, k)</span></div>
<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;  __shared__ BinaryType vecTile[kLanes][kLanes + 1]; <span class="comment">// avoid bank conflict</span></div>
<div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;</div>
<div class="line"><a name="l00039"></a><span class="lineno">   39</span>&#160;  WarpSelect&lt;int, int, false, Comparator&lt;int&gt;,</div>
<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;             NumWarpQ, NumThreadQ, kWarps * kLanes&gt;</div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    heap(kMaxDistance, -1, k);</div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;</div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;  <span class="keywordtype">int</span> warpId = threadIdx.y;</div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;  <span class="keywordtype">int</span> laneId = threadIdx.x;</div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;</div>
<div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;  <span class="comment">// Each warp handles a single query</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;  <span class="keywordtype">int</span> warpQuery = blockIdx.x * kWarps + warpId;</div>
<div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;  <span class="keywordtype">bool</span> queryInBounds = warpQuery &lt; query.getSize(0);</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;  <span class="comment">// Each warp loops through the entire chunk of vectors</span></div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> blockVec = 0; blockVec &lt; vecs.getSize(0); blockVec += kLanes) {</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;    <span class="keywordtype">int</span> threadDistance = 0;</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160;</div>
<div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    <span class="comment">// Reduction dimension</span></div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> blockK = 0; blockK &lt; vecs.getSize(1); blockK += kLanes) {</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;      <span class="keywordtype">int</span> laneK = blockK + laneId;</div>
<div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;      <span class="keywordtype">bool</span> kInBounds = laneK &lt; vecs.getSize(1);</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;      queryTile[warpId][laneId] = queryInBounds &amp;&amp; kInBounds ?</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;                               query[warpQuery][laneK] : 0;</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;      <span class="comment">// kWarps warps are responsible for loading 32 vecs</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; kLanes / kWarps; ++i) {</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;        <span class="keywordtype">int</span> warpVec = i * kWarps + warpId;</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;        <span class="keywordtype">int</span> vec = blockVec + warpVec;</div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;        <span class="keywordtype">bool</span> vecInBounds = vec &lt; vecs.getSize(0);</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        vecTile[warpVec][laneId] = vecInBounds &amp;&amp; kInBounds ?</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;                                 vecs[vec][laneK] : 0;</div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;      }</div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;      __syncthreads();</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;</div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;      <span class="comment">// Compare distances</span></div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;<span class="preprocessor"></span>      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; kLanes; ++i) {</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;        threadDistance += __popc(queryTile[warpId][i] ^ vecTile[laneId][i]);</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;      }</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;      __syncthreads();</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    }</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;</div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <span class="comment">// Lanes within a warp are different vec results against the same query</span></div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    <span class="comment">// Only submit distances which represent real (query, vec) pairs</span></div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    <span class="keywordtype">bool</span> valInBounds = queryInBounds &amp;&amp; (blockVec + laneId &lt; vecs.getSize(0));</div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    threadDistance = valInBounds ? threadDistance : kMaxDistance;</div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    <span class="keywordtype">int</span> <span class="keywordtype">id</span> = valInBounds ? blockVec + laneId : -1;</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;</div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    heap.add(threadDistance, <span class="keywordtype">id</span>);</div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;  }</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160;  heap.reduce();</div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;  <span class="keywordflow">if</span> (warpQuery &lt; query.getSize(0)) {</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;    heap.writeOut(outK[warpQuery].data(),</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;                  outV[warpQuery].data(),</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;                  k);</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160;  }</div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;}</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160;<span class="comment">// Version of the kernel that avoids a loop over the reduction dimension, and</span></div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;<span class="comment">// thus avoids reloading the query vectors</span></div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;<span class="keyword">template</span> &lt;<span class="keywordtype">int</span> NumWarpQ,</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;          <span class="keywordtype">int</span> NumThreadQ,</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;          <span class="keyword">typename</span> BinaryType,</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160;          <span class="keywordtype">int</span> ReductionLimit = kLanes&gt;</div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;__global__ <span class="keywordtype">void</span></div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;__launch_bounds__(kWarps * kLanes)</div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;binaryDistanceLimitSize(<span class="keyword">const</span> Tensor&lt;BinaryType, 2, true&gt; vecs,</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;                        <span class="keyword">const</span> Tensor&lt;BinaryType, 2, true&gt; query,</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;                        Tensor&lt;int, 2, true&gt; outK,</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;                        Tensor&lt;int, 2, true&gt; outV,</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;                        <span class="keywordtype">int</span> k) {</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;  <span class="comment">// A matrix tile (query, k)</span></div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;  __shared__ BinaryType queryTile[kWarps][kLanes + 1]; <span class="comment">// avoid bank conflict</span></div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160;</div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;  <span class="comment">// B matrix tile (vec, k)</span></div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;  __shared__ BinaryType vecTile[kLanes][kLanes + 1]; <span class="comment">// avoid bank conflict</span></div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;  WarpSelect&lt;int, int, false, Comparator&lt;int&gt;,</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;             NumWarpQ, NumThreadQ, kWarps * kLanes&gt;</div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    heap(kMaxDistance, -1, k);</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;  <span class="keywordtype">int</span> warpId = threadIdx.y;</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;  <span class="keywordtype">int</span> laneId = threadIdx.x;</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;  <span class="comment">// Each warp handles a single query</span></div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;  <span class="keywordtype">int</span> laneK = laneId;</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  <span class="keywordtype">int</span> warpQuery = blockIdx.x * kWarps + warpId;</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;  <span class="keywordtype">bool</span> kInBounds = laneK &lt; vecs.getSize(1);</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160;  <span class="keywordtype">bool</span> queryInBounds = warpQuery &lt; query.getSize(0);</div>
<div class="line"><a name="l00133"></a><span class="lineno">  133</span>&#160;</div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;</div>
<div class="line"><a name="l00135"></a><span class="lineno">  135</span>&#160;  queryTile[warpId][laneId] = queryInBounds &amp;&amp; kInBounds ?</div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;                                   query[warpQuery][laneK] : 0;</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  <span class="comment">// Each warp loops through the entire chunk of vectors</span></div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> blockVec = 0; blockVec &lt; vecs.getSize(0); blockVec += kLanes) {</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;    <span class="keywordtype">int</span> threadDistance = 0;</div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    <span class="comment">// kWarps warps are responsible for loading 32 vecs</span></div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;<span class="preprocessor"></span>    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; kLanes / kWarps; ++i) {</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;      <span class="keywordtype">int</span> warpVec = i * kWarps + warpId;</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;      <span class="keywordtype">int</span> vec = blockVec + warpVec;</div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;      <span class="keywordtype">bool</span> vecInBounds = vec &lt; vecs.getSize(0);</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;      vecTile[warpVec][laneId] = vecInBounds &amp;&amp; kInBounds ?</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;                               vecs[vec][laneK] : 0;</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;    }</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;    __syncthreads();</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160;</div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;    <span class="comment">// Compare distances</span></div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;<span class="preprocessor">#pragma unroll</span></div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;<span class="preprocessor"></span>    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; ReductionLimit; ++i) {</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160;      threadDistance += __popc(queryTile[warpId][i] ^ vecTile[laneId][i]);</div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;    }</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;    __syncthreads();</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160;</div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;    <span class="comment">// Lanes within a warp are different vec results against the same query</span></div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;    <span class="comment">// Only submit distances which represent real (query, vec) pairs</span></div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;    <span class="keywordtype">bool</span> valInBounds = queryInBounds &amp;&amp; (blockVec + laneId &lt; vecs.getSize(0));</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;    threadDistance = valInBounds ? threadDistance : kMaxDistance;</div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;    <span class="keywordtype">int</span> <span class="keywordtype">id</span> = valInBounds ? blockVec + laneId : -1;</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;    heap.add(threadDistance, <span class="keywordtype">id</span>);</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160;  }</div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;  heap.reduce();</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160;  <span class="keywordflow">if</span> (warpQuery &lt; query.getSize(0)) {</div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;    heap.writeOut(outK[warpQuery].data(),</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;                  outV[warpQuery].data(),</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;                  k);</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160;  }</div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;}</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> BinaryType&gt;</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160;<span class="keywordtype">void</span> runBinaryDistanceAnySize(Tensor&lt;BinaryType, 2, true&gt;&amp; vecs,</div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;                              Tensor&lt;BinaryType, 2, true&gt;&amp; query,</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;                              Tensor&lt;int, 2, true&gt;&amp; outK,</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;                              Tensor&lt;int, 2, true&gt;&amp; outV,</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;                              <span class="keywordtype">int</span> k, cudaStream_t stream) {</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160;  dim3 grid(utils::divUp(query.getSize(0), kWarps));</div>
<div class="line"><a name="l00188"></a><span class="lineno">  188</span>&#160;  dim3 block(kLanes, kWarps);</div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;</div>
<div class="line"><a name="l00190"></a><span class="lineno">  190</span>&#160;  <span class="keywordflow">if</span> (k == 1) {</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;    binaryDistanceAnySize&lt;1, 1, BinaryType&gt;</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 32) {</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;    binaryDistanceAnySize&lt;32, 2, BinaryType&gt;</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 64) {</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;    binaryDistanceAnySize&lt;64, 3, BinaryType&gt;</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 128) {</div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    binaryDistanceAnySize&lt;128, 3, BinaryType&gt;</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 256) {</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;    binaryDistanceAnySize&lt;256, 4, BinaryType&gt;</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 512) {</div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;    binaryDistanceAnySize&lt;512, 8, BinaryType&gt;</div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 1024) {</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    binaryDistanceAnySize&lt;1024, 8, BinaryType&gt;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  }</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;<span class="preprocessor">#if GPU_MAX_SELECTION_K &gt;= 2048</span></div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;<span class="preprocessor"></span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 2048) {</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;    binaryDistanceAnySize&lt;2048, 8, BinaryType&gt;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  }</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;<span class="preprocessor"></span>}</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;</div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> BinaryType, <span class="keywordtype">int</span> ReductionLimit&gt;</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;<span class="keywordtype">void</span> runBinaryDistanceLimitSize(Tensor&lt;BinaryType, 2, true&gt;&amp; vecs,</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;                                Tensor&lt;BinaryType, 2, true&gt;&amp; query,</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;                                Tensor&lt;int, 2, true&gt;&amp; outK,</div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;                                Tensor&lt;int, 2, true&gt;&amp; outV,</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;                                <span class="keywordtype">int</span> k, cudaStream_t stream) {</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;  dim3 grid(utils::divUp(query.getSize(0), kWarps));</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;  dim3 block(kLanes, kWarps);</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;  <span class="keywordflow">if</span> (k == 1) {</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    binaryDistanceLimitSize&lt;1, 1, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 32) {</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;    binaryDistanceLimitSize&lt;32, 2, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 64) {</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    binaryDistanceLimitSize&lt;64, 3, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 128) {</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;    binaryDistanceLimitSize&lt;128, 3, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 256) {</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;    binaryDistanceLimitSize&lt;256, 4, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 512) {</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;    binaryDistanceLimitSize&lt;512, 8, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 1024) {</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;    binaryDistanceLimitSize&lt;1024, 8, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;  }</div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;<span class="preprocessor">#if GPU_MAX_SELECTION_K &gt;= 2048</span></div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;<span class="preprocessor"></span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span> (k &lt;= 2048) {</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    binaryDistanceLimitSize&lt;2048, 8, BinaryType, ReductionLimit&gt;</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;      &lt;&lt;&lt;grid, block, 0, stream&gt;&gt;&gt;(</div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;      vecs, query, outK, outV, k);</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;  }</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;<span class="preprocessor"></span>}</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;<span class="keywordtype">void</span> runBinaryDistance(Tensor&lt;unsigned char, 2, true&gt;&amp; vecs,</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;                       Tensor&lt;unsigned char, 2, true&gt;&amp; query,</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;                       Tensor&lt;int, 2, true&gt;&amp; outK,</div>
<div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;                       Tensor&lt;int, 2, true&gt;&amp; outV,</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;                       <span class="keywordtype">int</span> k, cudaStream_t stream) {</div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;  FAISS_ASSERT(k &lt;= GPU_MAX_SELECTION_K);</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;  FAISS_ASSERT(vecs.getSize(1) == query.getSize(1));</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;  FAISS_ASSERT(outK.getSize(1) == k);</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;  FAISS_ASSERT(outV.getSize(1) == k);</div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;  <span class="comment">// For the optimized uint32 kernel, we handle 32 * 8 = 256 max dims</span></div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;  constexpr <span class="keywordtype">int</span> kReductionLimit32 = 8;</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;  <span class="comment">// For the optimized uint8 kernel, we handle 8 * 16 = 128 max dims</span></div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;  constexpr <span class="keywordtype">int</span> kReductionLimit8 = 16;</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;</div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;  <span class="comment">// All other cases (large or small) go through the general kernel</span></div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;  <span class="keywordflow">if</span> (vecs.getSize(1) % <span class="keyword">sizeof</span>(<span class="keywordtype">unsigned</span> int) == 0 &amp;&amp;</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;      (vecs.getSize(1) / <span class="keyword">sizeof</span>(<span class="keywordtype">unsigned</span> int)) &lt;= kReductionLimit32) {</div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    <span class="keyword">auto</span> vecs32 = vecs.castResize&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;();</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    <span class="keyword">auto</span> query32 = query.castResize&lt;<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>&gt;();</div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    <span class="comment">// Optimize for vectors with dimensions a multiple of 32 that are less than</span></div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;    <span class="comment">// 32 * kReductionLimit (256) dimensions in size</span></div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    runBinaryDistanceLimitSize&lt;unsigned int, kReductionLimit32&gt;(</div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;      vecs32, query32, outK, outV, k, stream);</div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (vecs.getSize(1) &lt;= kReductionLimit8) {</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    <span class="comment">// Optimize for vectors with dimensions a multiple of 32 that are less than</span></div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;    <span class="comment">// 32 * kReductionLimit (256) dimensions in size</span></div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    runBinaryDistanceLimitSize&lt;unsigned char, kReductionLimit8&gt;(</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;      vecs, query, outK, outV, k, stream);</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;  } <span class="keywordflow">else</span> {</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;    <span class="comment">// Arbitrary size kernel</span></div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;    runBinaryDistanceAnySize&lt;unsigned char&gt;(</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;      vecs, query, outK, outV, k, stream);</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;  }</div>
<div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;}</div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;</div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;} } <span class="comment">// namespace</span></div>
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